Model based optimal bit allocation

Modeling of the operational rate-distortion characteristics of a signal can significantly reduce the computational complexity of an optimal bit allocation algorithm. In this report, such models are studied

Classification of colon biopsy samples by spatial analysis of a single spectral band from its hyperspectral cube

The histopathological analysis of colon biopsy samples is a very important part of screening for colorectal cancer. There is, however, significant inter-observer and even intra-observer variability in the results of such analysis due to its very subjective nature. Therefore, quantitative methods are required for the analysis of histopathological images to aid the histopatholgists in their diagnosis. In this paper, we exploit the shape and structure of the gland nuclei cells for the classification of colon biopsy samples using two-dimensional principal component analysis (2DPCA) and Support Vector Machine (SVM). We conclude that the use of textural features extracted from non-overlapping blocks of the histopathological images results in a non-linear decision boundary which can be efficiently exploited using a SVM with appropriate choice of parameters for its Gaussian kernel. The SVM classifier outperforms all the remaining methods by a clear margin

Wavelet based segmentation of hyperspectral colon tissue imagery

Segmentation is an early stage for the automated classification of tissue cells between normal and malignant types. We present an algorithm for unsupervised segmentation of images of hyperspectral human colon tissue cells into their constituent parts by exploiting the spatial relationship between these constituent parts. This is done by employing a modification of the conventional wavelet based texture analysis, on the projection of hyperspectral image data in the first principal component direction. Results show that our algorithm is comparable to other more computationally intensive methods which exploit the spectral characteristics of the hyperspectral imagery data

Comparative analysis of spatial and transform domain methods for meningioma subtype classification

Pattern recognition in histopathological image analysis requires new techniques and methods. Various techniques have been presented and some state of the art techniques have been applied to complex textural data in histological images. In this paper, we compare the novel Adaptive Discriminant Wavelet Packet Transform (ADWPT) with a few prominent techniques in texture analysis namely Local Binary Patterns (LBP), Grey Level Co-occurrence Matrices (GLCMs) and Gabor Transforms. We show that ADWPT is a better technique for Meningioma subtype classification and produces classification accuracies of as high as 90%

Saving-investment Behaviour in Pakistan: An Empirical Investigation

This paper explores the saving-investment behaviour in Pakistan by identifying their patterns over time and across selected Asian countries. Further potential determinants were empirically tested, based on theoretical foundations of modelling for saving and investment behaviour. Savings in Pakistan for our sample period showed a positive response to GDP growth and government current expenditure while it remained insensitive to interest rates. On the other side, domestic savings and short-run expected returns positively affected investment whereas uncertainty reduced investment.saving Investment, Pakistan

Hyperspectral colon tissue cell classification

A novel algorithm to discriminate between normal and malignant tissue cells of the human colon is presented. The microscopic level images of human colon tissue cells were acquired using hyperspectral imaging technology at contiguous wavelength intervals of visible light. While hyperspectral imagery data provides a wealth of information, its large size normally means high computational processing complexity. Several methods exist to avoid the so-called curse of dimensionality and hence reduce the computational complexity. In this study, we experimented with Principal Component Analysis (PCA) and two modifications of Independent Component Analysis (ICA). In the first stage of the algorithm, the extracted components are used to separate four constituent parts of the colon tissue: nuclei, cytoplasm, lamina propria, and lumen. The segmentation is performed in an unsupervised fashion using the nearest centroid clustering algorithm. The segmented image is further used, in the second stage of the classification algorithm, to exploit the spatial relationship between the labeled constituent parts. Experimental results using supervised Support Vector Machines (SVM) classification based on multiscale morphological features reveal the discrimination between normal and malignant tissue cells with a reasonable degree of accuracy

Pension and Social Security Schemes in Pakistan : Some Policy Options

An examination of the public pension and social security schemes in Pakistan reveals that the provision of regular pensions is limited to formal sector employees only. A number of social security schemes that are operational in the public and private sectors cover a small proportion of old-age population, whereas a significant proportion of the elderly population working in the informal sector remains largely unprotected by social security schemes. As such, the challenge of meeting the needs of the increasing elderly population demands an improvement of the support base and social security system in Pakistan that emphasises the need to implement reforms of public pensions and programmes of social protection. Efficient deployment of resources and improvement of the governance structure are needed for effective welfare of the eligible sub-group of the elderly and the economically disadvantaged population.social security, Pensions, Pakistan

Pension and Social Security Schemes in Pakistan: Some Policy Options

An examination of the public pension and social security schemes in Pakistan reveals that the provision of regular pensions is limited to formal sector employees only. A number of social security schemes that are operational in the public and private sectors cover a small proportion of old-age population, whereas a significant proportion of the elderly population working in the informal sector remains largely unprotected by social security schemes. As such, the challenge of meeting the needs of the increasing elderly population demands an improvement of the support base and social security system in Pakistan that emphasises the need to implement reforms of public pensions and programmes of social protection. Efficient deployment of resources and improvement of the governance structure are needed for effective welfare of the eligible sub-group of the elderly and the economically disadvantaged population.Social Security, Pensions, Pakistan

Military Expenditures and Economic Growth in Pakistan

This paper explores the impacts of defence expenditures on economic growth and other major economic variables in the Pakistan economy over the period 1972-1995. The results of Granger-causality tests show that there is bi-directional feedback between the defence burden and GDP growth. We test four different single equation models that are widely used in the defence literature. In these frameworks we generally find the defence burden to be negatively related to GDP growth. Finally, we specify a three-equation model which explains GDP growth, average propensity to save, and the defence ratio. In single equation estimations of the savings ratio and the defence burden, we uncover some interesting relationships. The savings ratio is affected positively by the defence ratio, and negatively by the inflation rate. The Pakistani defence burden is impacted negatively by the Indian defence burden and positively by the government budget. When all three equations are estimated as a system to account for feedback and covariance between these equations, these effects are diminished and go down in statistical significance.

Personal Earnings Inequality in Pakistan: Findings from the HIES 1993-94

The earnings of workers play important role in the well-beings of households’ as they account for the largest proportion of total household income. If earnings of workers are distributed unevenly, they contribute significantly to the inequality in the household earnings. It may not be a cause of serious concern if income inequality grows and income of the workers also grows throughout the population and the position of the bottom segment improves. It is however serious when gap between rich and poor increases by worsening the position of poor. To reduce the household income inequality it is therefore important to focus on the distribution of personal earnings and frame a policy. There are many cause of inequality in personal earnings. As workers income rises at varying rates, it may reflect the decision of household of their investment in human capital and decisions to acquire skills. The factors like education, occupation, gender, regional location, sector of employment, and non-market forces such as discrimination may also play a significant role in the distribution of earnings.